PROF. THOMAS A. ADAMS IIPROF. THOMAS A. ADAMS IISustainable Energy System Design
PROF. VLADIMIR MAHALECPROF. VLADIMIR MAHALECOptimization, Planning & Scheduling
PROF. PRASHANT MHASKARPROF. PRASHANT MHASKARNonlinear Chemical Process Control
PROF. CHRIS SWARTZPROF. CHRIS SWARTZOptimal Operation & Design
one system at a time
Assistant Professor
Professor, Director of MACC Associate Professor
Professor
Solving the Energy Crisis
At the MACC, we are working to de-
velop new and innovative chemical
processes which improve the "triple-
bottom-line of sustainability",
meaning that the processes are not
only more environmentally friendly,
but also socially acceptable and yet
still economical. This can take several
forms, such as reducing or elim-
inating CO2 emissions at low cost, re-
ducing the amount of fossil fuels that
must be consumed, increasing the
use of renewable resources, reduc-
ing the "cradle-to-the-grave" life-
cycle impact of a process, or improv-
ing the thermal efficiency.
We are developing processes which
produce chemicals and energy in a
more sustainable way. This might in-
clude processes which use existing
technology in better ways (such as
polygeneration and gasification), or
processes which exploit up-and-com-
ing technologies (such as solid oxide
fuel cells, semicontinuous systems,
and nuclear-to-liquids). We use
state-of-the-art process simulations,
process synthesis techniques, strat-
egies for integrated design, control,
and optimization, life cycle impact
analyses, and techno-economic anal-
yses to create, investigate, and analyze
sustainable processes.
What’s HappeningPower Generation with No CO2
Solid oxide fuel cell systems, energy
storage, smart buildings, bulk power
Integrated Gasification, Reforming
Advanced flexible polygeneration
using natural gas, coal, and petcoke.
Sustainable Synthetic Fuels
Nuclear-to-liquids, bio-to-liquids
2nd
Generation Biofuel Processes
Thermochemical biobutanol, bioDME
Semicontinuous Distillation
Process intensification for low capital
Efficient and On Time
Process plant scheduling is a compu-
tationally difficult problem , even if the
plant behavior is described by approx-
imate nonlinear models. We have de-
veloped a novel scheduling algorithm
which enables rapid solutions of
large scale scheduling problems for
both linear and nonlinear processes.
The algorithm relies on inventory
pinch points along the scheduling
horizon to determine the regions
where optimal operating conditions
are constant. A discrete time period
planning model is used to optimize
allocation of swing storage and ass-
ociation of specific product ship-
ments with the product inventories. A
detailed schedule of operations is
then computed via continues time
scheduling model. The algorithm
computes solutions within times that
are 2 to 3 orders of magnitude shorter
than previously published research.
We have also developed an algorithm
that estimates of Bayesian networks
representing the production process,
which enables us to estimate the most
likely production time for each step.
Scheduling of production is then com-
puted by an algorithm which com-
bines linear programming with parallel
simulated annealing and frog leaping
evolutionary algorithms.
What’s HappeningProduction Scheduling
Inventory pinch point methods,
uncertainty in production times,
derivative-free optimization
Liquid Products Pipelines
Algorithms for large scale
scheduling and planning
Integrated Planning, Scheduling
Inventory pinch point methods for
long range production planning
Process and Power Distribution
Integrating chemical processes
with power production
Produce and deliver faster, better!
What’s Happening
Optimization plays a significant role
in MACC research projects. This inclu-
des formulation of a wide variety of
optimization problem types such as
linear programming, nonlinear pro-
gramming, mixed-integer program-
ming, dynamic optimization and glo-
bal optimization, and solution through
the application of state-of-the-art al-
gorithms and software. Many of the
problems exhibit features that make
them challenging to solve, such as
strong nonlinearity, high dimension,
discrete decisions, dynamic models,
model discontinuity and uncertainty.
Problems are formulated in different
modeling environments depending on
the application, and include GAMS,
AMPL, gPROMS, and Matlab. We also
develop novel formulations and sol-
ution approaches. Applications in-
clude nonlinear predictive control,
real-time optimization, supply chain
optimization, planning and schedul-
ing, integrated plant and control sys-
tem design, abnormal situation res-
ponse, and batch process operation
and control. We are currently working
with our industrial partners to apply
these techniques to steel refinery op-
erations, air separation systems, and
forestry supply chains.
Dynamic Operation
Approaches for large-scale problems,
parallel computing, uncertainty
Design for Dynamic Performance
Applications in cryogenic air
separation, Kraft pulp mills, electric
arc furnaces, supply chain systems
Real Time Optimization
Integration with model predictive
control. Transient applications
Optimal Planning & Scheduling
More economical plant operations
Control Your Most Difficult Processes
What’s Happening
processes to operate. For example, we
have developed the first systems
which detect when fault occurs and
then uses a Lyapunov-based model
predictive controller system to guide
the plant to a “safe-parking” state
where the fault can be remedied with-
out having to shut down the plant.
Other examples include integrated
control and optimization systems
which better handle high uncertain-
ty and process noise.
Quality process control is essential for
the successful operation of any chem-
ical process. At the MACC, we are
researching and developing cutting
edge control technologies to meet
the challenges of today's industry. We
are currently looking at process con-
trol for continuous and batch pro-
cesses; advanced model predictive
control techniques; strategies for de-
tecting and responding to process
faults using a safe-parking approach;
integrated optimization and control
strategies; and strategies for integr-
ated design and control. Advance-
ments in these areas are applied to
applications in energy, biofuels, and
bulk chemicals.
We are developing control systems
which address even the most difficult
Safe Parking Nonlinear Systems
Fault-tolerant control, handling of
failure conditions, Lyapunov MPC
Integrating Nonlinear Control
w/ Optimization-Based Control
Stabilizing nonlinear MPC,
handling uncertainty and noise,
energy system applications
Model Predictive Control for
Batch Systems & Bio-Systems
Safe-steering frameworks, reverse
time reachability regions
Keep it running when it counts! Optimization for maximum performance
The Biggest Bang for your Buck
Innovate
Photo credits: Jaffer Ghouse
Innovate.Collaborate.Collaborate.Innovate.
McMaster Advanced Control Consortium
2016 Industrial Brochure
Want More Information?
Contact Chris Swartz: (905) 525 9140 x 27945macc.mcmaster.ca [email protected]
Our Industrial Partners
The McMaster Advanced Control Consortium (MACC) was established in 1988 to promote and advance
process automation and related process systems engineering technologies through academe-industry
interactions. Company membership grew and also diversified, with current member companies spanning
the petroleum, chemical, steel, advanced materials, food
and control technology vendor industries.
The research is directed by six faculty members in the
McMaster Department of Chemical Engineering who
have a combined total of 48 years of industrial and 86
years of academic ex-perience. The remaining research
complement comprises of over 30 graduate students, research engineers, and postdoctoral fellows. The high
technical skills that MACC graduate students develop
through their course work at McMaster and their ind-
ustrially relevant research make them sought-after and
valuable assets to the process industries and their
technology suppliers.
MACC holds an annual research review meeting and
technical workshop, which provides and opportunity for
company representatives to learn about our research
directions and provide input, to learn about technical
details of the work at a graduate poster session, and to
participate in a technical workshop that provides depth
in a focussed technical area.
Through collaborative research projects, specific pro-
blems and/or areas of interest to an industrial partner
may be addressed. Benefits to industry include access to
in-depth analysis of the problem under consideration
with associated insights and understanding, low-cost
evaluation of potential benefits of new methodologies and applications, and early adoption of successful
technologies. Member companies have reported savings of millions of dollars per year, attributed to
interactions with the MACC.